At Bucher Municipal, much of the technical documentation, especially for older vehicle models, was only available in decentralised or paper form.
We want to use ChatGPT technology - but not in the cloud and certainly not without data control.
We deploy generative AI securely in your Azure environment. Fully under your control & GDPR-compliant.
Our data is stored in different systems and nobody knows how we can even use it with AI.
We connect your data sources in Azure and make them accessible for generative AI models - secure, structured and usable.
We are testing AI, but there is a lack of scaling - the models work well in the demo, but not in real operation.
We bring your AI projects into productive operation: stable, high-performance and Azure-optimised.
Why you can trust us
Data sovereignty in your own Azure environment
Availability for productive AI applications
Cloud lock-in through open architecture
Platform for secure AI solutions
Target group
Large companies, corporations
Markets
Germany, Austria, Switzerland
Technological basis
Microsoft Azure, OpenAI Service, Azure Machine Learning, Azure Cognitive Services
Complex data landscapes, high security requirements, lack of infrastructure? This is exactly what our Azure-based AI platform was developed for.
Our generative AI solution brings artificial intelligence to your company in a secure and scalable way. The solution is based on Microsoft Azure, integrates seamlessly into existing systems and fulfils the highest data protection and compliance standards.
If you want to use generative AI productively and keep your data under full control: Talk to us about your AI deployment in Azure.
The key difference between a standalone Azure environment and collana's solution lies in the enterprise maturity and feasibility of generative AI. We enhance Microsoft Azure with security, governance and practical deployment mechanisms that are not preconfigured in the standard system.
Azure with collana
Azure Standard
Data protection, role and rights management and GDPR compliance are integrated right from the start, without additional set-up effort or external tools.
Existing systems such as ERP, DMS or CRM are connected directly and made usable for AI models - without lengthy interface development.
The solution is optimised for high-load scenarios and grows with your needs - stable, high-performance and Azure-native.
From architecture to go-live: we provide maintenance, updates and technical support for your productive AI services.
Fast and secure provision of large language models and AI agents in Azure - preconfigured for productive use in the company.
Case Studies
At Bucher Municipal, much of the technical documentation, especially for older vehicle models, was only available in decentralised or paper form.
Implementation
We analyse your current Azure network structure (firewalls, VNets, landing zones) and identify the best approaches for integrating an LLM.
We design an AI architecture with options: Standard LLM (Azure OpenAI) or open source model - each to suit your requirements.
In an isolated, non-productive environment, we demonstrate the technical feasibility of the selected AI use case for your company.
Now comes the system connection: the AI solution is connected to your existing systems (ERP, databases, etc.) and made operational.
We provide you with long-term support: monitoring, updates, optimisations and extensions to your Azure AI infrastructure are all part of our service.
Technology used
Azure OpenAI Service
Azure Machine Learning
Azure Cognitive Services
Azure Active Directory / Entra ID
Recommendation
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Questions about generative AI in Azure
A generative AI solution in Microsoft Azure enables companies to operate generative AI models securely and scalably in the Azure cloud. It combines the Azure OpenAI Service with defined architecture, governance and security standards and supports the productive use of AI - from technical integration to operation in the corporate environment.
The solution is aimed at large companies and corporations with high data protection, compliance and system integration requirements. It is particularly suitable for organisations that want to integrate generative AI into existing IT landscapes such as ERP, CRM or DMS systems.
In contrast to a pure Azure deployment, the solution provides a preconfigured architecture for the secure operation of large language models. This includes governance mechanisms, monitoring, cost control and the structured integration of AI into existing business processes.
Yes, data processing takes place within the Azure environment of the respective company, without access from external providers. The architecture fulfils European data protection requirements such as the GDPR and uses security mechanisms such as encryption, role-based access controls and the use of Azure Key Vault.